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return response
frmt = Format(mime_type='application/gml', extension=".gml") # this is unknown mimetype
return Process(handler=complex_proces,
identifier='my_complex_process',
title='Complex process',
inputs=[
ComplexInput(
'complex',
'Complex input',
default="DEFAULT COMPLEX DATA",
supported_formats=[frmt])
],
outputs=[
ComplexOutput(
'complex',
'Complex output',
supported_formats=[frmt])
])
outputs = [
ComplexOutput("output_archive", "Tar archive",
abstract="Tar archive of the netCDF files storing the index values.",
supported_formats=[Format("application/x-tar")],
as_reference=True,
),
ComplexOutput('ncout', 'Example netCDF file',
abstract="NetCDF file storing the index computed over one dataset.",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]
),
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format("text/plain")])
]
super(IndicessingleProcess, self).__init__(
self._handler,
identifier="indices_single",
title="Climate indices (Single variable)",
version="0.10",
abstract="Climate index calculated from one daily input variable.",
metadata=[
{'title': 'Doc',
'href': 'http://flyingpigeon.readthedocs.io/en/latest/descriptions/\
index.html#climate-indices'},
{"title": "ICCLIM",
abstract='User name for the COPERNICUS Sci-hub authentication.',
# default='2013-12-31',
min_occurs=1,
max_occurs=1,
),
LiteralInput('password', 'Password',
data_type='string',
abstract='Password for the COPERNICUS Sci-hub authentification.',
min_occurs=1,
max_occurs=1,
),
]
outputs = [
ComplexOutput("output", "Fetched Files",
abstract="File containing the local paths to downloaded files.",
supported_formats=[Format('text/plain')],
as_reference=True,
),
ComplexOutput("output_log", "Logging information",
abstract="Collected logs during process run.",
supported_formats=[Format("text/plain")],
as_reference=True,
)
]
super(EO_COP_fetchProcess, self).__init__(
self._handler,
identifier="EO_COP_fetch",
title="EO COPERNICUS Fetch Resources",
LiteralInput("coords", "Coordinates",
abstract="A comma-seperated tuple of WGS85 lon,lat decimal coordinates (e.g. 2.356138, 48.846450)", # noqa
default="2.356138, 48.846450",
data_type='string',
min_occurs=1,
max_occurs=100,
),
]
outputs = [
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain')]
),
ComplexOutput('tarout', 'Subsets',
abstract="Tar archive containing the netCDF files",
as_reference=True,
supported_formats=[Format('application/x-tar')]
),
]
super(PointinspectionProcess, self).__init__(
self._handler,
identifier="pointinspection",
title="Point Inspection",
abstract='Extract the timeseries at the given coordinates.',
version="0.10",
metadata=[
Metadata('LSCE', 'http://www.lsce.ipsl.fr/en/index.php'),
Metadata('Doc', 'http://flyingpigeon.readthedocs.io/en/latest/'),
],
max_occurs=1)
]
outputs = [
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain')]
),
ComplexOutput('output', 'Links to regridded dataset',
abstract="JSON file listing the regridded netCDF URLs.",
as_reference=True,
supported_formats=[json_format]
),
ComplexOutput('output_netcdf', 'NetCDF file',
abstract="First NetCDF file generated by process.",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]
),
]
super(ESMFRegridProcess, self).__init__(
self._handler,
identifier="esmf_regrid",
title="ESMF regridding",
abstract='Regrid netCDF files to a destination grid.',
version="0.10",
metadata=[
Metadata('Doc', 'http://flyingpigeon.readthedocs.io/en/latest/'),
],
inputs=inputs,
max_occurs=1000,
supported_formats=[
Format('application/x-netcdf'),
Format('application/x-tar'),
Format('application/zip'),
]),
]
outputs = [
ComplexOutput('output', 'Tar archive',
abstract="Tar archive of the subsetted netCDF files.",
as_reference=True,
supported_formats=[Format('application/x-tar')]
),
ComplexOutput('ncout', 'Example netCDF file',
abstract="NetCDF file with subset for one dataset.",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]
),
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain')]
)
]
super(ClipregionseuropeProcess, self).__init__(
self._handler,
identifier="subset_regionseurope",
title="Subset (European Regions)",
'1971-2000', '1981-2010']
),
LiteralInput("archive_format", "Archive format",
abstract="Result files will be compressed into archives.\
Choose an appropriate format",
default="tar",
data_type='string',
min_occurs=1,
max_occurs=1,
allowed_values=['zip', 'tar']
)
]
outputs = [
ComplexOutput("output_gbif", "Graphic of GBIF coordinates",
abstract="PNG graphic file showing the presence of tree species\
according to the CSV file",
supported_formats=[Format('image/png')],
as_reference=True,
),
ComplexOutput("output_PA", "Graphic of PA mask",
abstract="PNG graphic file showing PA mask generated based on\
netCDF spatial increment",
supported_formats=[Format('image/png')],
as_reference=True,
),
ComplexOutput("output_reference", "Climate indices for growth conditions of reference period",
abstract="Archive (tar/zip) containing calculated climate indices",
supported_formats=[Format('application/x-tar'),
]
outputs = [
# ComplexOutput('output_log', 'Logging information',
# abstract="Collected logs during process run.",
# as_reference=True,
# supported_formats=[Format('text/plain')]
# ),
#
# ComplexOutput("plotout_spaghetti", "Visualisation, Spaghetti plot",
# abstract="Visualisation of single variables as a spaghetti plot",
# supported_formats=[Format("image/png")],
# as_reference=True,
# ),
ComplexOutput("plotout_uncertainty", "Visualisation Uncertainty plot",
abstract="Visualisation of single variables ensemble running mean with uncertainty",
supported_formats=[Format("image/png")],
as_reference=True,
)
# TODO: include window for running mean
]
super(PlotuncertaintyProcess, self).__init__(
self._handler,
identifier="plot_uncertainty",
title="Timeseries as uncertainty plot",
version="0.1",
metadata=[
Metadata('Doc',
'https://flyingpigeon.readthedocs.io/en/latest/processes_des.html#data-visualization'),
],
]
"""
LiteralInput('dedrizzle', 'De-drizzle',
abstract="Whether to remove the precipitation drizzle.",
min_occurs=0,
max_occurs=1,
default='False',
data_type='bool'),
LiteralInput('norm', 'Normalization transformation',
abstract="Transformation to apply before mapping.",
default='identity',
allowed_values=["identifty", "zscore", "boxcox"],
data_type='string'),
"""
outputs = [
ComplexOutput('output_netcdf_ref', 'Bias-corrected ref dataset.',
as_reference=True,
supported_formats=[Format('application/x-netcdf'),]
),
ComplexOutput('output_netcdf_fut', 'Bias-corrected fut dataset.',
as_reference=True,
supported_formats=[Format('application/x-netcdf'),]
),
ComplexOutput('output_log', 'Logging information',
abstract="Collected logs during process run.",
as_reference=True,
supported_formats=[Format('text/plain'),]
),
]
super(KDDM_BC_Process, self).__init__(
self._handler,
]
outputs = [
ComplexOutput("analog_pdf", "Maps with mean analogs and simulation",
abstract="Analogs Maps",
supported_formats=[Format('image/pdf')],
as_reference=True,
),
ComplexOutput("config", "Config File",
abstract="Config file used for the Fortran process",
supported_formats=[Format("text/plain")],
as_reference=True,
),
ComplexOutput("analogs", "Analogues File",
abstract="mulit-column text file",
as_reference=True,
supported_formats=[Format("text/plain")],
),
ComplexOutput("formated_analogs", "Formated Analogues File",
abstract="Formated analogues file for viewer",
supported_formats=[Format("text/plain")],
as_reference=True,
),
ComplexOutput('output_netcdf', 'Subsets for one dataset',
abstract="Prepared netCDF file as input for weatherregime calculation",
as_reference=True,
supported_formats=[Format('application/x-netcdf')]
),